scholarly journals A Technical Critique of Some Parts of the Free Energy Principle

Entropy ◽  
2021 ◽  
Vol 23 (3) ◽  
pp. 293
Author(s):  
Martin Biehl ◽  
Felix A. Pollock ◽  
Ryota Kanai
Keyword(s):  
Free Energy ◽  
Equations Of Motion ◽  
Conditional Density ◽  
Original Formulation ◽  
Energy Principle ◽  
Free Energy Principle ◽  
Technical Issues ◽  
Generalised Coordinates ◽  
Markov Blankets ◽  
Rule Out

We summarize the original formulation of the free energy principle and highlight some technical issues. We discuss how these issues affect related results involving generalised coordinates and, where appropriate, mention consequences for and reveal, up to now unacknowledged, differences from newer formulations of the free energy principle. In particular, we reveal that various definitions of the “Markov blanket” proposed in different works are not equivalent. We show that crucial steps in the free energy argument, which involve rewriting the equations of motion of systems with Markov blankets, are not generally correct without additional (previously unstated) assumptions. We prove by counterexamples that the original free energy lemma, when taken at face value, is wrong. We show further that this free energy lemma, when it does hold, implies the equality of variational density and ergodic conditional density. The interpretation in terms of Bayesian inference hinges on this point, and we hence conclude that it is not sufficiently justified. Additionally, we highlight that the variational densities presented in newer formulations of the free energy principle and lemma are parametrised by different variables than in older works, leading to a substantially different interpretation of the theory. Note that we only highlight some specific problems in the discussed publications. These problems do not rule out conclusively that the general ideas behind the free energy principle are worth pursuing.

scholarly journals The Markov blankets of life: autonomy, active inference and the free energy principle

2018 ◽  
Vol 15 (138) ◽  
pp. 20170792 ◽  
Author(s):  
Michael Kirchhoff ◽  
Thomas Parr ◽  
Ensor Palacios ◽  
Karl Friston ◽  
Julian Kiverstein
Keyword(s):  
Free Energy ◽  
Biological Systems ◽  
Autonomous Systems ◽  
Living Organism ◽  
Active Inference ◽  
Energy Principle ◽  
Free Energy Principle ◽  
Markov Blanket ◽  
Markov Blankets ◽  
The Way

This work addresses the autonomous organization of biological systems. It does so by considering the boundaries of biological systems, from individual cells to Home sapiens , in terms of the presence of Markov blankets under the active inference scheme—a corollary of the free energy principle. A Markov blanket defines the boundaries of a system in a statistical sense. Here we consider how a collective of Markov blankets can self-assemble into a global system that itself has a Markov blanket; thereby providing an illustration of how autonomous systems can be understood as having layers of nested and self-sustaining boundaries. This allows us to show that: (i) any living system is a Markov blanketed system and (ii) the boundaries of such systems need not be co-extensive with the biophysical boundaries of a living organism. In other words, autonomous systems are hierarchically composed of Markov blankets of Markov blankets—all the way down to individual cells, all the way up to you and me, and all the way out to include elements of the local environment.

scholarly journals The Emperor's New Markov Blankets

2021 ◽  
pp. 1-63
Author(s):  
Jelle Bruineberg ◽  
Krzysztof Dolega ◽  
Joe Dewhurst ◽  
Manuel Baltieri
Keyword(s):  
Free Energy ◽  
Mathematical Framework ◽  
Active Inference ◽  
Energy Principle ◽  
Free Energy Principle ◽  
Variational Free Energy ◽  
Standard Application ◽  
The Mind ◽  
Physical Boundary ◽  
Markov Blankets

Abstract The free energy principle, an influential framework in computational neuroscience and theoretical neurobiology, starts from the assumption that living systems ensure adaptive exchanges with their environment by minimizing the objective function of variational free energy. Following this premise, it claims to deliver a promising integration of the life sciences. In recent work, Markov Blankets, one of the central constructs of the free energy principle, have been applied to resolve debates central to philosophy (such as demarcating the boundaries of the mind). The aim of this paper is twofold. First, we trace the development of Markov blankets starting from their standard application in Bayesian networks, via variational inference, to their use in the literature on active inference. We then identify a persistent confusion in the literature between the formal use of Markov blankets as an epistemic tool for Bayesian inference, and their novel metaphysical use in the free energy framework to demarcate the physical boundary between an agent and its environment. Consequently, we propose to distinguish between ‘Pearl blankets’ to refer to the original epistemic use of Markov blankets and ‘Friston blankets’ to refer to the new metaphysical construct. Second, we use this distinction to critically assess claims resting on the application of Markov blankets to philosophical problems. We suggest that this literature would do well in differentiating between two different research programs: ‘inference with a model’ and ‘inference within a model’. Only the latter is capable of doing metaphysical work with Markov blankets, but requires additional philosophical premises and cannot be justified by an appeal to the success of the mathematical framework alone.

Encultured minds, not error reduction minds

2020 ◽  
Vol 43 ◽  
Author(s):  
Robert Mirski ◽  
Mark H. Bickhard ◽  
David Eck ◽  
Arkadiusz Gut
Keyword(s):  
Free Energy ◽  
Error Reduction ◽  
Energy Principle ◽  
Free Energy Principle ◽  
Current Article

Abstract There are serious theoretical problems with the free-energy principle model, which are shown in the current article. We discuss the proposed model's inability to account for culturally emergent normativities, and point out the foundational issues that we claim this inability stems from.

scholarly journals Modelling ourselves: what the free energy principle reveals about our implicit notions of representation

Synthese ◽  
2021 ◽  
Author(s):  
Matt Sims ◽  
Giovanni Pezzulo
Keyword(s):  
Free Energy ◽  
Philosophy Of Mind ◽  
Predictive Processing ◽  
Energy Principle ◽  
Philosophical Debate ◽  
Free Energy Principle ◽  
Self Organized ◽  
Functional Aspects ◽  
Structural Content ◽  
Unified View

AbstractPredictive processing theories are increasingly popular in philosophy of mind; such process theories often gain support from the Free Energy Principle (FEP)—a normative principle for adaptive self-organized systems. Yet there is a current and much discussed debate about conflicting philosophical interpretations of FEP, e.g., representational versus non-representational. Here we argue that these different interpretations depend on implicit assumptions about what qualifies (or fails to qualify) as representational. We deploy the Free Energy Principle (FEP) instrumentally to distinguish four main notions of representation, which focus on organizational, structural, content-related and functional aspects, respectively. The various ways that these different aspects matter in arriving at representational or non-representational interpretations of the Free Energy Principle are discussed. We also discuss how the Free Energy Principle may be seen as a unified view where terms that traditionally belong to different ontologies—e.g., notions of model and expectation versus notions of autopoiesis and synchronization—can be harmonized. However, rather than attempting to settle the representationalist versus non-representationalist debate and reveal something about what representations are simpliciter, this paper demonstrates how the Free Energy Principle may be used to reveal something about those partaking in the debate; namely, what our hidden assumptions about what representations are—assumptions that act as sometimes antithetical starting points in this persistent philosophical debate.

scholarly journals Is free-energy minimisation the mark of the cognitive?

2021 ◽  
Vol 36 (2) ◽  
Author(s):  
Julian Kiverstein ◽  
Matt Sims
Keyword(s):  
Nervous System ◽  
Free Energy ◽  
Problem Solving ◽  
Living Systems ◽  
Energy Principle ◽  
Free Energy Principle ◽  
Energy Minimisation ◽  
Long Run ◽  
Evolution Of Life ◽  
Mark Of The Cognitive

AbstractA mark of the cognitive should allow us to specify theoretical principles for demarcating cognitive from non-cognitive causes of behaviour in organisms. Specific criteria are required to settle the question of when in the evolution of life cognition first emerged. An answer to this question should however avoid two pitfalls. It should avoid overintellectualising the minds of other organisms, ascribing to them cognitive capacities for which they have no need given the lives they lead within the niches they inhabit. But equally it should do justice to the remarkable flexibility and adaptiveness that can be observed in the behaviour of microorganisms that do not have a nervous system. We should resist seeking non-cognitive explanations of behaviour simply because an organism fails to exhibit human-like feats of thinking, reasoning and problem-solving. We will show how Karl Friston’s Free-Energy Principle (FEP) can serve as the basis for a mark of the cognitive that avoids the twin pitfalls of overintellectualising or underestimating the cognitive achievements of evolutionarily primitive organisms. The FEP purports to describe principles of organisation that any organism must instantiate if it is to remain well-adapted to its environment. Living systems from plants and microorganisms all the way up to humans act in ways that tend in the long run to minimise free energy. If the FEP provides a mark of the cognitive, as we will argue it does, it mandates that cognition should indeed be ascribed to plants, microorganisms and other organisms that lack a nervous system.

scholarly journals A universal ethology challenge to the free energy principle: species of inference and good regulators

2021 ◽  
Vol 36 (2) ◽  
Author(s):  
Michael D. Kirchhoff ◽  
Thomas van Es
Keyword(s):  
Free Energy ◽  
Energy Principle ◽  
Free Energy Principle

Learned Uncertainty: A Free Energy Principle Perspective on Anxiety

2021 ◽  
Author(s):  
Hugh McGovern ◽  
Alexander De Foe ◽  
Pantelis Leptourgos ◽  
Philip R. Corlett ◽  
Kavindu Bandara ◽  
...  
Keyword(s):  
Free Energy ◽  
Anxiety Disorder ◽  
Biological System ◽  
Predictive Modelling ◽  
Generative Models ◽  
Generalized Anxiety ◽  
Unified Theory ◽  
Cognitive Mechanisms ◽  
Energy Principle ◽  
Free Energy Principle

Generalized Anxiety Disorder (GAD) is among the world’s most prevalent psychiatric disorders. Affecting an eighth of the world’s population, it often manifests as persistent apprehension which is difficult to control. Despite its prevalence, neuroscientific efforts to understand the cognitive mechanisms of GAD remain sparse. This has resulted in a fractured theoretical landscape, lacking a unitary framework. While prior theories of anxiety describe the cognitive, affective and behavioral dimensions of anxiety, a unified theory is lacking. Here, we point out that postulates derived from the Free Energy Principle (FEP) may allow for a unified theory to emerge. We argue an approach focused on predictive modelling may afford opportunities to re-conceptualize anxiety within the framework of working generative models, rather than static beliefs. We suggest that a biological system—having had persistent uncertainty in its past—will form posteriors in line with uncertainty in its future, irrespective of whether that uncertainty is real. After discussing the FEP, we explain how anxiety develops through learning uncertainty before suggesting predictions for how the model can be tested.

A Curiosity Algorithm for Robots Based on the Free Energy Principle

2021 ◽  
Vol 2021 (0) ◽  
pp. 1P1-I18
Author(s):  
Daisuke KAWAHARA ◽  
Sara OZEKI ◽  
Ikuo MIZUUCHI
Keyword(s):  
Free Energy ◽  
Energy Principle ◽  
Free Energy Principle

Species of Realization and the Free Energy Principle

2014 ◽  
Vol 93 (4) ◽  
pp. 706-723 ◽  
Author(s):  
Michael D. Kirchhoff
Keyword(s):  
Free Energy ◽  
Energy Principle ◽  
Free Energy Principle

Generalization of Fuels Swelling Data by Means of Linear Free Energy Principle

2014 ◽  
pp. 125-149
Author(s):  
Roman Makitra ◽  
Halyna Midyana ◽  
Liliya Bazylyak ◽  
Olena Palchykova
Keyword(s):  
Free Energy ◽  
Energy Principle ◽  
Free Energy Principle ◽  
Linear Free Energy
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